Structure

Physi-Chem Properties

Molecular Weight:  516.06
Volume:  417.512
LogP:  4.976
LogD:  4.249
LogS:  -4.786
# Rotatable Bonds:  5
TPSA:  49.69
# H-Bond Aceptor:  3
# H-Bond Donor:  2
# Rings:  2
# Heavy Atoms:  6

MedChem Properties

QED Drug-Likeness Score:  0.479
Synthetic Accessibility Score:  5.304
Fsp3:  1.0
Lipinski Rule-of-5:  Accepted
Pfizer Rule:  Rejected
GSK Rule:  Rejected
BMS Rule:  2
Golden Triangle Rule:  Rejected
Chelating Alert:  0
PAINS Alert:  0

ADMET Properties (ADMETlab2.0)

ADMET: Absorption

Caco-2 Permeability:  -4.761
MDCK Permeability:  1.5456995242857374e-05
Pgp-inhibitor:  0.94
Pgp-substrate:  0.0
Human Intestinal Absorption (HIA):  0.028
20% Bioavailability (F20%):  0.494
30% Bioavailability (F30%):  0.799

ADMET: Distribution

Blood-Brain-Barrier Penetration (BBB):  0.207
Plasma Protein Binding (PPB):  97.43071746826172%
Volume Distribution (VD):  1.111
Pgp-substrate:  5.104163646697998%

ADMET: Metabolism

CYP1A2-inhibitor:  0.069
CYP1A2-substrate:  0.853
CYP2C19-inhibitor:  0.376
CYP2C19-substrate:  0.929
CYP2C9-inhibitor:  0.861
CYP2C9-substrate:  0.218
CYP2D6-inhibitor:  0.004
CYP2D6-substrate:  0.181
CYP3A4-inhibitor:  0.465
CYP3A4-substrate:  0.907

ADMET: Excretion

Clearance (CL):  5.875
Half-life (T1/2):  0.26

ADMET: Toxicity

hERG Blockers:  0.016
Human Hepatotoxicity (H-HT):  0.734
Drug-inuced Liver Injury (DILI):  0.05
AMES Toxicity:  0.08
Rat Oral Acute Toxicity:  0.481
Maximum Recommended Daily Dose:  0.407
Skin Sensitization:  0.419
Carcinogencity:  0.279
Eye Corrosion:  0.79
Eye Irritation:  0.137
Respiratory Toxicity:  0.983

Download Data

Data Type Select
General Info & Identifiers & Properties  
Structure MOL file  
Source Organisms  
Biological Activities  
Similar NPs/Drugs  

  Natural Product: NPC294445

Natural Product ID:  NPC294445
Common Name*:   LSOZDDIWYCQPCC-FQJWRULHSA-N
IUPAC Name:   n.a.
Synonyms:  
Standard InCHIKey:  LSOZDDIWYCQPCC-FQJWRULHSA-N
Standard InCHI:  InChI=1S/C20H35Br2ClO3/c1-17(2)13(18(3,25)9-7-14(17)21)6-10-19(4)15(22)8-11-20(5,26-19)16(24)12-23/h13-16,24-25H,6-12H2,1-5H3/t13-,14-,15-,16-,18-,19+,20+/m1/s1
SMILES:  CC1(C)[C@@H](CC[C@@]2(C)[C@@H](CC[C@@](C)([C@@H](CCl)O)O2)Br)[C@@](C)(CC[C@H]1Br)O
Synthetic Gene Cluster:   n.a.
ChEMBL Identifier:   n.a.
PubChem CID:   23425507
Chemical Classification**:  
  • CHEMONTID:0000000 [Organic compounds]
    • [CHEMONTID:0000012] Lipids and lipid-like molecules
      • [CHEMONTID:0000259] Prenol lipids
        • [CHEMONTID:0001550] Sesquiterpenoids

*Note: the InCHIKey will be temporarily assigned as the "Common Name" if no IUPAC name or alternative short name is available.
**Note: the Chemical Classification was calculated by NPClassifier Version 1.5. Reference: PMID:34662515.

  Species Source

Organism ID Organism Name Taxonomy Level Family SuperKingdom Isolation Part Collection Location Collection Time Reference
NPO8821 Delphinium dictyocarpum Species Ranunculaceae Eukaryota n.a. n.a. n.a. Database[HerDing]
NPO2491 Laurencia obtusa Species Rhodomelaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO8821 Delphinium dictyocarpum Species Ranunculaceae Eukaryota n.a. n.a. n.a. Database[TCMID]
NPO18938 Ladeania juncea Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO15600 Trifolium pannonicum Species Fabaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO13493 Mauremys reevesii Species Geoemydidae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO2329 Scutellaria glabra Species Lamiaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO1221 Juniperus serawschanica Species Cupressaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO666 Cymbidium aloifolium Species Orchidaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO5527 Ligularia atroviolacea Species Asteraceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO10341 Pseudogymnoascus pannorum Species Pseudeurotiaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO2491 Laurencia obtusa Species Rhodomelaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO8821 Delphinium dictyocarpum Species Ranunculaceae Eukaryota n.a. n.a. n.a. Database[UNPD]
NPO1054 Peucedanum graveolens Species Apiaceae Eukaryota n.a. n.a. n.a. Database[UNPD]

☑ Note for Reference:
In addition to directly collecting NP source organism data from primary literature (where reference will provided as NCBI PMID or DOI links), NPASS also integrated them from below databases:
UNPD: Universal Natural Products Database [PMID: 23638153].
StreptomeDB: a database of streptomycetes natural products [PMID: 33051671].
TM-MC: a database of medicinal materials and chemical compounds in Northeast Asian traditional medicine [PMID: 26156871].
TCM@Taiwan: a Traditional Chinese Medicine database [PMID: 21253603].
TCMID: a Traditional Chinese Medicine database [PMID: 29106634].
TCMSP: The traditional Chinese medicine systems pharmacology database and analysis platform [PMID: 24735618].
HerDing: a herb recommendation system to treat diseases using genes and chemicals [PMID: 26980517].
MetaboLights: a metabolomics database [PMID: 27010336].
FooDB: a database of constituents, chemistry and biology of food species [www.foodb.ca].

  NP Quantity Composition/Concentration

Organism ID NP ID Organism Material Preparation Organism Part NP Quantity (Standard) NP Quantity (Minimum) NP Quantity (Maximum) Quantity Unit Reference

☑ Note for Reference:
In addition to directly collecting NP quantitative data from primary literature (where reference will provided as NCBI PMID or DOI links), NPASS also integrated NP quantitative records for specific NP domains (e.g., NPS from foods or herbs) from domain-specific databases. These databases include:
DUKE: Dr. Duke's Phytochemical and Ethnobotanical Databases.
PHENOL EXPLORER: is the first comprehensive database on polyphenol content in foods [PMID: 24103452], its homepage can be accessed at here.
FooDB: a database of constituents, chemistry and biology of food species [www.foodb.ca].

  Biological Activity

Target ID Target Type Target Name Target Organism Activity Type Activity Relation Value Unit Reference

☑ Note for Activity Records:
☉ The quantitative biological activities were primarily integrated from ChEMBL (Version-30) database and were also directly collected from PubMed literature. PubMed PMID was provided as the reference link for each activity record.

  Chemically structural similarity: I. Similar Active Natural Products in NPASS

Top-200 similar NPs were calculated against the active-NP-set (includes 4,3285 NPs with experimentally-derived bioactivity available in NPASS)

Similarity level is defined by Tanimoto coefficient (Tc) between two molecules. Tc lies between [0, 1] where '1' indicates the highest similarity. What is Tanimoto coefficient

●  The left chart: Distribution of similarity level between NPC294445 and all remaining natural products in the NPASS database.
●  The right table: Most similar natural products (Tc>=0.56 or Top200).

Similarity Score Similarity Level Natural Product ID

  Chemically structural similarity: II. Similar Clinical/Approved Drugs

Similarity level is defined by Tanimoto coefficient (Tc) between two molecules.

●  The left chart: Distribution of similarity level between NPC294445 and all drugs/candidates.
●  The right table: Most similar clinical/approved drugs (Tc>=0.56 or Top200).

Similarity Score Similarity Level Drug ID Developmental Stage

  Bioactivity similarity: Similar Natural Products in NPASS

Bioactivity similarity was calculated based on bioactivity descriptors of compounds. The bioactivity descriptors were calculated by a recently developed AI algorithm Chemical Checker (CC) [Nature Biotechnology, 38:1087–1096, 2020; Nature Communications, 12:3932, 2021], which evaluated bioactivity similarities at five levels:
A: chemistry similarity;
B: biological targets similarity;
C: networks similarity;
D: cell-based bioactivity similarity;
E: similarity based on clinical data.

Those 5 categories of CC bioactivity descriptors were calculated and then subjected to manifold projection using UMAP algorithm, to project all NPs on a 2-Dimensional space. The current NP was highlighted with a small circle in the 2-D map. Below figures: left-to-right, A-to-E.

A: chemistry similarity
B: biological targets similarity
C: networks similarity
D: cell-based bioactivity similarity
E: similarity based on clinical data